Today marks the release of ISAcreator 1.7.9. It’s been a long time coming having been more than 2 years since the last update to the ISA framework’s flagship ISA-Tab creator and editor software.

Included in this release, we have addressed a range of bugs with fixes covering UI issues, file path handling errors, and cross-platform issues with bug reports from our Windows users. With this release, we want to demonstrate to our valued user community that development and maintenance of ISAcreator is still active and continues to be the de-facto editor for the ISA-Tab format.

We’re very pleased to announce today the version 0.5 release of the Python ISA API, where the work started almost 2 years ago.

The ISA API aims to provide software developers with a set of tools to help you easily and quickly build your own ISA objects, validate, and convert between serializations of ISA-formatted datasets and other formats/schemas (e.g. SRA schemas). The ISA API is published on PyPI as the isatools package. The vision for the ISA API is to provide a programming library that will become the core for all software tooling that supports the ISA framework. It enables the import of various data formats into an implementation of the ISA Abstract Model as Python objects, and export of ISA content from Python objects back to different serialization formats.

Currently we support import of ISA-Tab, ISA JSON, SRA XML (European Nucleotide Archive), Metabolomics Workbench, Biocrates XML and mzML formats, and export to ISA-Tab, ISA JSON and SRA XML. Beyond enabling I/O of data, the ISA API also supports programmatic creation of ISA content through the Python ISA model objects directly, thus then being able to export ISA content in the aforementioned serialization formats. This means that you can use the ISA API in your own software tools to create ISA-Tab and ISA JSON. You can see the ISA API in action in this example creating a simple ISA-Tab.

Since the ISA API is available as a Python library in the isatools PyPI package (just install with pip install isatools), it can easily be integrated with Python ecosystem infrastructure such as iPython’s interactive computing environment and Jupyter, a web application that allows you to create and share documents that contain live Python code are more. We are also developing ISA API containers using Docker, via the Horizon 2020 PhenoMeNal project, to run various function from the isatools package on the Cloud.

This version 0.5 release marks a significant milestone as the ISA Team has put a lot of effort into developing various I/O and ISA content creation features. Now we are looking to scale up and make robust the ISA API with thorough performance and user testing as we work towards a version 1.0 release.

The ISA API is still in development and as an open-source project we would be very happy to receive any help and code contributions (testing, feature requests, pull requests). Please feel free to contact our development team at isatools@googlegroups.com or on the ISA Community Forum Google Group, or ask a question, report a bug or request a new feature in the GitHub issue tracker.

The original ISA-Tab specification was published as a Release Candidate document in 2008, documenting the initial work that forms the ISA framework, with a further update in 2009. Since then, we have done work on a new serialization in JSON, ISA-JSON, and abstracted out the data model from both the tabular and JSON formats.

The ISA Model and Serialization Specifications consist of three specification documents:

ISA Abstract Model – a data model of ISA objects/entities and their relation to one another

Back in April this year, Dr David Johnson from the ISA team gave a presentation on “Data Infrastructures to Foster Data Reuse” at a workshop on Integrating Large Data into Plant Science: From Big Data to Discovery hosted by GARnet (the UK network for Arabidopsis researchers) and Egenis (the Exeter Centre for the Study of the Life Sciences). The workshop was held at Dartington Hall in Devon, South West England, and was well attended by researchers from the plant and biological science community worldwide as well as representatives from industry from organisations such as Syngenta.

David presented on ISA, as well as on biosharing.org, as candidate data infrastructure resources for enabling data reuse in the plant sciences, as well as presenting an example of how one might encode high-throughput plant phenotyping in ISA tab.

We have observed the uptake of the ISA tab format across the broad range of life sciences, but view its adoption, with a view to making data FAIR (Findable, Accessible, Interoperable and Reusable), in the plant sciences as essential for the field. In particular centres such as the UK’s National Plant Phenomics Centre in Aberystwyth, Wales, could benefit hugely from adopting ISA where there are emerging challenges in data management, in particular as automation of data collection is a significant driver in modern plant-based research and agritech.

There are also existing data analysis platforms such as Araport (the Arabidopsis information Portal), TAIR (The Arabidopsis Information Resources) and BioDare (Biological Data Repository) that could benefit from standardizing their experimental data, as well as ongoing efforts to create open data resources in the plant sciences, such as the Collaborative Open Plant Omics (COPO) project, that will be using the new ISA JSON format as native data objects.

Today, March 15 2016, the FAIR Guiding Principles for scientific data management and stewardship were formally published in the Nature Publishing Group journal Scientific Data. The problem the FAIR Principles address is the lack of widely shared, clearly articulated, and broadly applicable best practices around the publication of scientific data. While the history of scholarly publication in journals is long and well established, the same cannot be said of formal data publication. Yet, data could be considered the primary output of scientific research, and its publication and reuse is necessary to ensure validity, reproducibility, and to drive further discoveries. The FAIR Principles address these needs by providing a precise and measurable set of qualities a good data publication should exhibit – qualities that ensure that the data is Findable, Accessible, Interoperable, and Reusable (FAIR).

The ISA infrastructure project and BioSharing registry of standards, databases and policies are both part of this community in which we strive to make data FAIR. Do join us in these efforts!

We are very happy to announced that Dr David Johnson and Dr Massimiliano Izzo have joined the ISA team as a Research Software Engineers, last year and this year, respectively.

David and Massi are both great additions to the team. A few words about their past experience…

David

David completed his PhD at the University of Reading (UK) and before joining us at the University of Oxford e-Research Centre (OeRC), he worked at Imperial College London where he was a founding member of the Data Science Institute. Prior to that he worked in the Department of Computer Science at Oxford University, where he was part of an FP7 project developing interoperable cancer model databases, and also in the Evolutionary Biology Group at the University of Reading where he developed high-performance computing software for phylogenetics. He serves on the technical programme committees of a number of international conferences including the International Conference on Computational Science series and on the editorial board of the journal Cancer Informatics.

Massi

Massi completed PhD studies in Biomedical Engineering at the University of Genoa (Italy). His main interests are in the design and development of innovative data models for Life Sciences, structured/unstructured data management and full-stack software development (JavaScript all the way!). Before joining the OeRC, he was a Research Collaborator at the Giannini Gaslini Institute, in Genoa (Italy) where he developed distributed data management systems for Integrated Biobanking Management, mostly targeted to Paediatric Tumours. In his free time, Massi enjoys reading (mostly speculative fiction novels), gazing at the ceiling while lying on the sofa, and wander aimlessly in bookshops and cafes.

In this post, Dr David Johnson gives his reflection on an ISA specification hackathon held in July 2015, in advance of joining the ISA team at Oxford as a research software engineer.

Last week I joined my prospective colleagues at the Oxford University e-Research Centre (OeRC) with some of their collaborators to thresh out an evolution of the ISA (Investigation/Study/Assay) metadata tracking framework. I will be joining the ISA development team at Oxford from September this year, which is a new phase in my career that I am very much looking forward to.

ISA consists of a model specification that describes its key concept elements and structure, while implementations of the specification are also developed by the ISA team. The framework aims to facilitate standards-compliant collection, curation, management and reuse of datasets in the life sciences. The first version of the specification, a Release Candidate from 2008, is implemented as the ISA-Tab (tabular) format – a table-based format that many working in the life sciences are used to, where data is abundantly stored and manipulated in spreadsheets. More recently ISA can also be converted to RDF via linkedISA.

Redefining the spec to define the ‘core’ ISA elements and separating out domain specific ‘extensions’

Specifying conventions, mechanisms, and best practices for developing extensions to this new ‘ISA core’.

What was clear was that there was plenty of scope for evolving ISA from various parts of the user community. By abstracting out the core ISA specification, what we need now is contributions from a diverse range of exemplar projects to ensure that the core is truly interoperable. To this end, we are now encouraging communities to share their ISA templates along with exemplar experiments and start building a repository of extensions in the ISA commons website. In the meantime the ISA team will be formalising the ISA core and developing new reference implementations in tabular and JSON formats and supporting tools. We hope to have a draft specification presented to the community in the fall of 2015.

Apart from the 3 days of discussions fuelled by much coffee and cake, we did also find some time in the evenings to get out to enjoy the sunshine and enjoy a couple of Oxford’s wonderful restaurants…

One of my key takeaways from the workshop, apart from having a crash course into the ISA spec that I will be working on in the coming months, is the importance of going through the community engagement process when developing a data specification. As with engineering software, we need to make sure we are building the right thing. Soliciting feedback is not a vanity exercise or even a political exercise, but an essential part of a carefully-managed process to ensure we evolve the specification to fulfil the changing needs of the people that matter – the user community.

We are happy to announce the release of OntoMaton, a tool which allows users to search for ontology terms and tag free text right in Google Spreadsheets. This post will serve to introduce you to the tool, how it works and how it can make it easier for users to use ontologies in a pervasive, powerful and collaborative environment, complementing existing work from our team in the creation of ISAcreator.

How it looks

OntoMaton is available from the Google Script Gallery and when installed provides a menu as shown below.

From the menu you may access two resources part of OntoMaton: ontology search and ontology tagging. There is also an ‘about’ option.

Ontology Search

Ontology Tagging

Behind the scenes: restricting the ontology search space

If a sheet named “restrictions” is in your spreadsheet, OntoMaton will consult it to determine if the currently selected column/row name has a narrowed ontology search space. This makes it quicker to search BioPortal, allows for restriction of the user’s result space to make easier the process of selecting a term.

Behind the scenes: extra information about the terms you select

For every term you select, it’s full details are recorded in a “terms” sheet. This makes it possible to use OntoMaton in any spreadsheet and all provenance information (including URIs, ontology source and version) for selected ontology terms will be immediately available for use when exposing your records to the linked data world!

Installing

To install, create a new google spreadsheet, then go to the menu tools > script gallery. In the script gallery, search for ontology or ontomaton and you’ll get the following result pane.

Click on ‘install’ and this will install the scripts inside your spreadsheet. Then there is one more and final step to follow for installation. You have to click again on tools > script manager and you’ll be presented with something like that shown in the image below.

OntoMaton contains lots of functions, but the only one you need to worry about in order to run the program is the onOpen function. Click this then click on run and the OntoMaton menu will be installed in your menu bar. From here you’ll be able to access the ontology search and ontology tagging functions.

OntoMaton inherently supports ISA-Tab files too. So if you have an investigation file it will automatically add ontology sources to the ONTOLOGY SOURCE REFERENCE block. Also, if you have Term Source Ref and Term Source Accession after a column, OntoMaton will automatically populate these columns for you.

Also, the following table provides a quick review of available tools attempting to mix spreadsheets and access to vocabulary servers:

domain

automated

annotation

ontology search/lookup

versioning*

collaboration

RightField

general

✘

✓

✘

✘

ISA creator

multiomics

✓

✓

✘

✘

Proteome Harvest PRIDE

proteomics

✘

✓

✘

✘

Annotare

transcriptomics

✘

✘

✓

✘

OntoMaton

general

✓

✓

✓

✓

by versioning we refer to managing of user edits throughout the annotation process.

We hope you enjoy this new feature!

The ISA team

Addendum:

Safari 6 users, be aware you will have to activate the ‘developer menu’ from the Advanced Item in the Safari ‘Preferences’ menu item. Once activated, go to menu ‘Develop’ and navigate to ‘User Agent’ item and select ‘Safari 5.1.7’ for enabling the browser to work with Google Spreadsheet. (Thanks to rpyzh for reporting the issue, see here)

The ISA team is very happy to announce that Alejandra has joined the ISA team as a software engineer. Alejandra will add a great deal to our team and we’re especially looking forward to her contributions in our semantic web & linked data work.

You can follow her on Github where Alejandra will be putting all of her code or on Twitter.